ICBCCR: A new path for harmonization and clinical verification on a multi-center real-world cohort of 278703.

IF 2.9 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
Penghui Zhang, Zhiwu Dong, Yingting Wu, Lufei Jiang, Huiling Fang, Xue Yuan, Houqun Ying, Chong Chen, Xin Chang, Xinxin Ren, Manman Zhang, Wenqing Chu, Lianxiang Xing, Keliang Huang, Weiyi Wu, Yuqing Zhu
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引用次数: 0

Abstract

Background: In this study, we aimed to develop a novel harmonization algorithm to achieve the conversion from current results to harmonized results directly and perform a clinical verification on a multi-center real-world cohort of 278,703.

Methods: Sixty patient samples were collected as harmonization reference materials to develop and internally validate the harmonization algorithm. We assessed the harmonization effectiveness through multiple dimensions such as method comparison and evaluation. Then, the harmonization algorithm was performed on 278,703 sample results. We compared the distributions of the harmonized results from different in vitro diagnostic measurement devices through the Bhattacharyya distance.

Results: After harmonized by the novel algorithm, equivalent results were obtained among 5 in vitro diagnostic measurement devices for MYO with mean percent differences from -1.5 % to -0.1 % and the 95 % limits of agreement from 14.1 % to 20.3 % and for CK-MB with mean percent differences from -0.2 % to 1.1 % and the 95 % limits of agreement from 14.5 % to 36.6 %. The coefficients of variation of the results for the same sample presented a significant decrease from 20.6 % to 4.6 % for MYO and from 38.6 % to 5.3 % for CK-MB. Furthermore, after the harmonization algorithm was performed on 278,703 sample results from the real world, the Bhattacharyya distance decreased from 0.0046 to 0.0019 for MYO and from 0.0949 to 0.0049 for CK-MB after harmonization, respectively.

Conclusions: The novel algorithm is a new path for harmonization only based on current results and its clinical applicability has been fully verified in the real world.

ICBCCR:在278703个多中心真实队列中协调和临床验证的新途径
背景:在本研究中,我们旨在开发一种新的协调算法,以实现从当前结果到协调结果的直接转换,并在278,703个多中心真实世界队列中进行临床验证。方法:采集60例患者标本作为协调基准,制定协调算法并进行内部验证。通过方法比较和评价等多个维度对协调效果进行了评价。然后,对278,703个样本结果进行协调算法。我们通过Bhattacharyya距离比较了不同体外诊断测量装置的协调结果的分布。结果:和谐的新颖的算法后,相当于5体外诊断测量设备之间结果MYO的平均百分比差异从-1.5 % -0.1 %和95年 %限制的协议14.1 % 20.3 %和水平的平均百分比差异从-0.2 % 1.1 %和95年 %限制的协议14.5 % 36.6 %。同一样品的变异系数MYO从20.6 %下降到4.6 %,CK-MB从38.6 %下降到5.3 %。此外,对278,703个真实世界的样本结果进行调和算法后,调和后的MYO和CK-MB的Bhattacharyya距离分别从0.0046和0.0949降至0.0019和0.0049。结论:该算法仅基于目前的结果,是一条新的协调路径,其临床适用性已在现实世界中得到充分验证。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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